Optimization of a bogie primary suspension damping to reduce wear in railway operations

An optimization problem is formulated to attain the vector of optimized primary suspension passive dampers of a bogiein order to minimize wear in railway applications. A mechanical system with five degrees of freedom (DOF) comprising a single rigid wheelset attached to a fixed bogie frame is chosen to explore the effects of primary suspension damping components on wear. Different operational scenarios including tangent and curved tracks together with different levels of track irregularities are introduced to be used as inputs to model. The equations of motion of the system are obtained and the FASTSIM algorithm is employed to relate the creepages and the corresponding creep forces in different directions. At vehicle maximum admissible speed and a given set of operational scenarios, the optimized values of the primary suspension passive dampers in longitudinal, lateral and vertical directions are found through a genetic algorithm optimization routine in MATLAB. The outcomes of current research can not only be used to minimize wear in railway operation as well as reduce track access charges and maintenance costs, but also give insight into designingadaptive bogies

Towards adaptive bogie design

Suspension components play a crucial role in bogie dynamics behavior. In this regard, passive and active systems are developed to meet various design requirements. Adaptive suspension systems can adjust the bogie dynamics with respect to different operational scenarios and as a result improve the vehicle performance. Therefore, there is a great demand on design of adaptive suspension systems for high speed train bogies. Sensitivity analysis, optimization, and active vibration control techniques are the most important steps towards adaptive bogie design. In this thesis, the target is to cover these steps partly by formulating and solving the prescribed problems for some example railway vehicle models. Therefore, hierarchical levels of vehicle modelling are considered. The overall performance of a vehicle can be evaluated from different perspectives. In this thesis, the dynamics behaviour of railway vehicles is reflected by ride comfort, wear, safety, and in particular running stability, track shift force, and risk of derailment objective functions. The mathematical representation of the prescribed objectives as well as the evaluation procedure are described thoroughly. As an example on optimization problem with application in railway vehicles, the comfort/safety multiobjective optimization of a one car vehicle lateral dampers is considered. The genetic algorithm routine is used to solve this problem. In order to have a better wear estimation, a theoretical contact search approach is applied to calculate the creepages and wear. The optimization problem of primary dampers towards wear showed that one might achieve better wear performance by using active technology in bogie primary suspension components. Therefore, different on/off semi-active control strategies are integrated together with the magnetorheological dampers in bogie primary suspension and the corresponding effects on wear is explored on different operational scenarios. Finally, to have a better insight into adaptive bogie design, the global sensitivity analysis of bogie dynamics behavior with respect to suspension components is considered. The multiplicative version of the dimension reduction method is employed to provide the sensitivity indices. The result of such analysis can narrow down the number of input variables for the optimization and adaptive bogie design problems and improve the computational efficiency. All in all, this thesis deals with formulating and solving some example problems on the sensitivity analysis and optimization of railway vehicles. Furthermore, as an introduction to active bogie systems, the application of semi-active vibration control strategies in bogie primary suspension is also considered. The results of the current thesis can provide useful hints in design of adaptive suspension system for high speed train bogies

Towards adaptive bogie design

Suspension components play a crucial role in bogie dynamics behavior. In this regard, passive and active systems are developed to meet various design requirements. Adaptive suspension systems can adjust the bogie dynamics with respect to different operational scenarios and as a result improve the vehicle performance. Therefore, there is a great demand on design of adaptive suspension systems for high speed train bogies. Sensitivity analysis, optimization, and active vibration control techniques are the most important steps towards adaptive bogie design. In this thesis, the target is to cover these steps partly by formulating and solving the prescribed problems for some example railway vehicle models. Therefore, hierarchical levels of vehicle modelling are considered. The overall performance of a vehicle can be evaluated from different perspectives. In this thesis, the dynamics behaviour of railway vehicles is reflected by ride comfort, wear, safety, and in particular running stability, track shift force, and risk of derailment objective functions. The mathematical representation of the prescribed objectives as well as the evaluation procedure are described thoroughly. As an example on optimization problem with application in railway vehicles, the comfort/safety multiobjective optimization of a one car vehicle lateral dampers is considered. The genetic algorithm routine is used to solve this problem. In order to have a better wear estimation, a theoretical contact search approach is applied to calculate the creepages and wear. The optimization problem of primary dampers towards wear showed that one might achieve better wear performance by using active technology in bogie primary suspension components. Therefore, different on/off semi-active control strategies are integrated together with the magnetorheological dampers in bogie primary suspension and the corresponding effects on wear is explored on different operational scenarios. Finally, to have a better insight into adaptive bogie design, the global sensitivity analysis of bogie dynamics behavior with respect to suspension components is considered. The multiplicative version of the dimension reduction method is employed to provide the sensitivity indices. The result of such analysis can narrow down the number of input variables for the optimization and adaptive bogie design problems and improve the computational efficiency. All in all, this thesis deals with formulating and solving some example problems on the sensitivity analysis and optimization of railway vehicles. Furthermore, as an introduction to active bogie systems, the application of semi-active vibration control strategies in bogie primary suspension is also considered. The results of the current thesis can provide useful hints in design of adaptive suspension system for high speed train bogies

Multiobjective Optimisation and Active Control of Bogie Suspension

Railways provide fast, safe, clean, and cheap transportation service. The cost efficiency inrailway operations can be scrutinized from different perspectives. Here, passenger ride comfort,wheel/rail contact wear, and safety (in particular running stability, track shift force, and risk ofderailment) are considered as objective functions introduced to evaluate the dynamics behaviourof railway vehicles. Running speed also plays a key role in cost efficiency of railway operations.Higher speeds shorten journey time and make railways more competitive with other types oftransportation systems. However, this might increase wear and deteriorate ride comfort andsafety. To improve the performance in railway operations advanced designs and technologiesare developed during the past decades. Bogie primary and secondary suspension systems of highspeed trains can significantly affect the dynamics behaviour of the vehicle. Such componentsmight have conflicting effects on different objective functions. It is important to have theoptimum performance of suspension components. In this regard, one of the ultimate goals of thisthesis is to improve the vehicle performance from different points of views by studying passiveand active suspension systems and using multiobjective optimisation techniques to meetconflicting design requirements. Computational cost is one of the main challenges inmultidisciplinary design optimisation. The computational efforts for optimisation can besignificantly mitigated by narrowing down the number of input design parameters. Here, anefficient global sensitivity analysis is carried out to identify those suspension components thathave prominent influences on different objective functions. Based on the global sensitivityanalysis results obtained two multiobjective optimisation problems are formulated and solved.First, multiobjective optimisation of bogie suspension components with respect to safety toimprove running speed on curves. Second problem is to reduce wear and improve ride comfortwhen the vehicle is operating with the enhanced speeds. Consequently, the vehicle runs secureand faster with higher ride comfort and less wear by means of the two optimisation problemssolved. The optimisations are carried out using the genetic algorithm. In the case of safetyoptimisation problem, semi active control strategies are also applied using magnetorheologicaldampers and the effects on the dynamics behaviour are explored. The robustness of the bogiesuspension Pareto optimised solutions against uncertainties in the design parameters is alsostudied. Active control technology is one of the main targets of this thesis. In this regard, a robustcontroller is designed using the H∞ control technique to stabilize the wheel set motion andimprove curving performance. The controller is robust against track irregularities. Finally, theactuator dynamics is considered and a compensation technique is applied to reduce the actuator’stime delay and improve the performance

Robustness analysis of bogie suspension components Pareto optimised values

Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway opera- tions from different perspectives. Uncertainties in the design param- eters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto opti- mised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1

Application of Semi-Active Control Strategies in Bogie Primary Suspension System

Primary suspension components of high speed train bogies can affect the vehicle\u27s performance from different points of view, such as wear reduction and increasing forward speed to decrease track access charges. Various types of suspension components, as well as several control techniques, have been developed to amend the cost efficiency of railway operation; with respect to speed, wear, ride comfort, and safety. In the current study, the research overview is laid out with focus on the state-of-the-art, introducing semi-active technology for primary suspension of a bogie for high speed trains. The dynamic behaviour of a one car vehicle model developed in SIMPACK running on various operational scenarios including tangent and curved tracks is considered. The focus is to investigate the effects of passive and different semi-active control strategies on wear. For the passive case, an optimization problem is formulated to find the values of design parameters that guarantee minimum wear in system, while safety and comfort are taken as thresholds. Primary longitudinal and lateral stiffness as well as the primary suspension damper characteristics are chosen as design parameters and genetic algorithm based optimization routine in MATLAB is employed to solve the optimization problems. The attained optimized suspension parameters are applied in a one car railway vehicle model that is developed to be used as a reference case for comparison for the semi-active vibration control techniques. Application of magnetorheological (MR) dampers in the bogie\u27s primary suspension, integrated with several semi-active on-off control strategies, is investigated. The outcomes of this research can amend the cost efficiency of railway operation (especially reduce wear) and give some hints for the design process of adaptive bogies

Pareto Optimization of a Nonlinear Tuned Mass Damper to Control Vibrations in Hand Held Impact Machines

Large amplitude vibrations from hand held impact machines might bring serious health problems for users in long term. Here, a vibration absorber which works based on the nonlinear tuned mass damper concept is applied to mitigate unpleasant vibrations in a hand held impact machine. A global sensitivity analysis is carried out using multiplicative dimensional reduction method to scrutinize the effects of different components on the hand held impact machine dynamics response and attenuate the number of input parameters for optimization. Based on the global sensitivity analysis results, the nonlinear tuned mass damper components are chosen as the design parameters subject to optimization. A multiobjective optimization problem is formulated and solved using genetic algorithm to reduce vibrations and total weight of the machine. The Pareto optimized solutions are robust against the exciting force amplitude and frequency. The global sensitivity analysis results revealed that it is possible to run the simulations with a constant exciting force amplitude and extend the obtained solutions for the case with a variable exciting force amplitude while the same order of accuracy in the results can be observed. This significantly reduced the computational burden of the optimization. Closed form expressions for the optimal values of the tuned mass damper parameters as well as system response in terms of the auxiliary mass are developed by using the nonlinear least squares method. The results revealed that the proposed technique can significantly suppress the vibrations induced by the hand held impact machine. This makes it possible for users to operate the machine for a longer time period with lower health risks

Multiobjective optimisation of bogie suspension to boost speed on curves

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. Track shift force, running stability, and risk of derailment are selected as safety objective functions. To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm and MATLAB/SIMPACK co-simulation is executed at three levels.The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems

Global sensitivity analysis and multiobjective optimization of bogie suspension

Multiobjective optimization of nonlinear multibody systems with many degrees of freedom is a burdensome computational challenge.A feasible practical methodology for global sensitivity analysis (GSA) of multibody systems with respect to design parameters is proposed basedon the multiplicative dimensional reduction method. The computational efficiency of optimization is significantly improved by restricting theinput design parameters only to those identified by the GSA. The methodology is applied for GSA of a railway vehicle dynamics with respect tothe bogie suspension characteristics. Several multiobjective optimization problems are then formulated and solved for a railway vehicle modelwith 50 degrees of freedom using genetic algorithm. The results obtained yield practical information regarding the optimized bogie suspensionproperties which improve the dynamics behaviour of the vehicle from various perspectives. The proposed algorithm can be used in designoptimization of nonlinear multibody systems with different applications

Towards Optimal Design of Engineering Systems

The paper presents a review on methods, algorithms and tools available for robust optimal design of engineering systems. The focus primarily is put on methods and algorithms for global sensitivity analysis (GSA) and solution of Pareto optimization problems (POP) for multidimensional nonlinear\ua0 mechanical systems. The computer code SAMO, developed at Chalmers University of Technology, is presented as an efficient toolbox for optimal design ofengineering systems with different applications. At this stage, the toolbox SAMO includes two modules: SAMO-GSA and SAMO-POP. The module SAMO-GSA is developed based on the multiplicative version of the dimensional reduction method. In the SAMO-GSA an efficient approximation is employed to simplify the computation of variance-based sensitivity indices associated with a general function of n-random variables. The GSA results of the engineering system in question are then presented as a mapping of the design parameters and the total sensitivity indices of the objective functions. These results might be used as an input to the SAMO-POP for multi-objective optimization. The module SAMO-POP works based on genetic algorithm (GA). The GA settings include lower and upper bounds for variation of the design parameters, population size, number of generations, elite count, and Pareto fraction settings. The results of SAMO-POP are presented in terms of Pareto fronts and corresponding Pareto sets for further analysis and decision making by the user. The efficiency of the proposed algorithms and developed toolbox is illustrated, first on scholar applications (thermally induced stress intensity factor and quarter car vehicle model), and second by GSA and solutions of several multi-objective optimization problems for a nonlinear multidimensional mechanical system which represents bogie suspension components of a high-speed train. Finally, based on the literature review and the results obtained the paper presents the outlook of the future research in developing of computationally efficient algorithms for extension of the toolboxSAMO for robust optimal design of engineering systems